AI Technical Product Manager
Listed on 2026-02-24
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer
Who we are…
YOOBIC is an AI-powered frontline employee experience platform. Our mobile app gives business leaders and frontline teams the performance tools they need to communicate, learn, and work—all in one place. With streamlined communications, mobile learning, and digitized task management, YOOBIC drives operational excellence while drastically improving the frontline employee working experience. 350+ companies around the world including Mattress Firm, Michaels, Game Stop, Lacoste, Lidl, Boots, Peloton, Pret, Puma, and Vans trust YOOBIC to improve operational consistency and agility, get real-time visibility into multi-location business execution, and improve customer experience.
To learn more about YOOBIC, visit or follow us on Linked In.
We’re hiring a AI Tech Product Manager to rapidly prototype and validate AI-powered product ideas, then handover to ML Engineering for industrialization. You’ll pair a product mindset with hands‑on Python
, data‑centric ML
, and LLM‑centric prototyping (prompting via APIs, chaining treatments, and building simple user interfaces for user testing) to turn promising concepts into testable, value‑proven prototypes—fast. You’ll collaborate closely with Product Managers and Designers, and work with ML Engineers, our AI/ML Architect, and AI/ML Researcher to bring the right ideas to life.
Scope opportunities with PMs and Designers; frame problems and success criteria before solutioning.
Prototype quickly using two equally important approaches
:LLM‑centric prototyping
: prompt LLMs via API, chain treatments/tools/agents, and develop simple user interfaces to enable rapid user testing and feedback loops.Data‑centric ML in Python
: feature engineering, dataset curation, model selection, training, evaluation, and error analysis to validate feasibility and impact beyond “just calling an API.”
Assess feasibility & value (technical + product), run lightweight experiments, and capture learnings.
Translate wins into briefs & delivery plans and handover to ML Engineers for productionization; partner through design/QA.
Track impact post‑launch with the product team (adoption, quality, and business KPIs).
Strong Python and ML foundations; able to build workable prototypes (Num Py/pandas/scikit‑learn; PyTorch a plus).
Proven feature engineering and data‑centric ML skills (problem decomposition, robust evaluation, error analysis).
Equally strong LLM prototyping skills:
prompting via APIs
, tool/agent orchestration and chaining
, and building simple UIs (e.g., lightweight web apps or internal panels) for user testing.Experience with
no‑code/workflow tools (e.g., n8n) to accelerate experiments; solid prompt/agent design.Product mindset: ability to frame problems, run experiments, and communicate clearly with technical and non‑technical partners.
Excellent English communication; proactive, self‑organized remote collaborator.
Familiarity with FastAPI/Docker/cloud for local validation (you won’t own MLOps/industrialization).
Prior experience in SaaS product management or technical product roles.
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